Energy Efficiency Assessment of Model Predictive Adaptive Cruise Control for a Light-Duty Commercial Fuel Cell Electric Vehicle

The integration of Advanced Driver Assistance Systems (ADAS) with Energy Management Strategies (EMS) represents an emerging research domain for modern Hybrid Electric Vehicles (HEVs). Within this category, Fuel Cell Electric Vehicles (FCEVs) incorporating a high-voltage (HV) battery and a fuel cell (FC) stack present a compelling case study for developing integrated controllers that optimize onboard energy flow from power sources to vehicle dynamics. A key research challenge in this field concerns the assessment of longitudinal dynamics controllers’ impact on vehicle energy efficiency, which is being investigated in this work through controller development and experimental validation. This work presents the deployment of an Adaptive Cruise Control (ACC) system based on Model Predictive Control (MPC) on a light-duty commercial FCEV. The objective is to design and experimentally validate a computationally efficient longitudinal dynamics controller while evaluating its potential for improving energy efficiency and passengers’ comfort. The proposed approach has been evaluated in simulation on the model of a light-duty commercial FCEV validated experimentally on a chassis dynamometer testbed. Results demonstrate that optimizing the vehicle’s speed profile achieved up to a 5% reduction in energy consumption while maintaining operational timing constraints and passengers’ comfort requirements.